Roadmap to High Throughput Phenotyping for Plant Breeding

被引:23
作者
Kim J.Y. [1 ]
机构
[1] USDA-ARS, Arid-Land Agricultural Research Center, 21881 North Cardon Lane, Maricopa, 85138, AZ
关键词
Breeding; Data Management; Image processing; Phenotyping; Sensors;
D O I
10.1007/s42853-020-00043-0
中图分类号
学科分类号
摘要
Background: Population growth and climate uncertainty increase the demand for more food to feed the world. Finding a new variety and discovering novel genetic traits that confer stress tolerance will be a game changer in future crop production for sustainable agriculture. Developing and implementing high throughput phenotyping (HTP) technologies and skills become increasingly important to those involved with applying genomics in breeding and biotechnology research. Many institutes and private companies are initiating HTP programs to improve the quality and speed of plant breeding and biotechnology. Breeders and plant scientists need to secure solid data pipelines of phenotypes throughout years-long breeding programs, but they lack an engineering background on sensors, image processing, data management, and cloud-running architecture. Purpose: There are a series of components and steps that must be considered for HTP programs to meet their needs and goals. Those components include sensors, platforms, analytics, and data management. The aim of this paper is to address key information of what plant breeding is, why HTP is important, and how the HTP system is designed. Review: The paper describes background of plant science to engineering to enlighten the need of HTP and provides a review of the current HTP systems and future strategies. Discussion includes specifics of each HTP component to consider and a roadmap to HTP for plant breeding throughout genetics, phenotypic metrics, algorithm development, data standardization, and scale-up. © 2020, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.
引用
收藏
页码:43 / 55
页数:12
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